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- Wydział Matematyki Fizyki i Informatyki UG
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application! We are looking for a postdoctoral researcher to work on the fundamentals of knowledge graphs and virtual data integration. Work assignments You will actively participate and lead work tasks in two
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We invite you to apply for a 2-year postdoctoral position in the area of hybrid AI, combining modern language models (LMs) with ontologies and knowledge graphs (KGs). The position is part of a newly
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) Your main responsabilities : To carry out research missions in the field of graph generation under constraints To ensure supervision and tutoring missions To contribute to the reputation of the School
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate
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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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curriculum vitae of each nominee (if available, mandatory for self-nominations Please note that any further documents or appendices (like tables, graphs, etc.) will not be considered in the evaluation
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, graphs); experience with analysis and processing of large volumes of data; development of reproducible scientific software; proficiency in Python and libraries (Pandas/NumPy and PyTorch/TensorFlow/Scikit
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate therapeutic target identification. GenePPS aims to overcome current limitations of perturbation modelling